Median algorithm for estimating the variance of intrinsic noise when detecting a signal with an unknown initial phase

Abstract

The article presents the finding of the dispersion of intrinsic noise distributed according to Rayleigh's law to find a signal with an unknown initial phase according to the Neumann- Pearson criterion. This algorithm is used for primary signal processing. The practical significance of the work is the study of the basics of programming in C and Python, comparison and identification of the advantages of this algorithm in comparison with the evaluation by the average value method. It also shows the finding of the threshold at which a decision is made to detect a useful signal. In this work, the integrated programming environment Visual studio was used – a popular environment for writing, debugging and compiling code. It also contains most of the libraries used, which simplify the writing of code. And Anaconda is a distribution for the Python programming language, which includes a set of free libraries, which is also freely available. Using the C language, the task of calculating data and filling it into an array was performed, Python was used for modeling, constructing histograms and comparing the results obtained with theoretical ones. This work can be used for teaching students of higher educational institutions for the purpose of familiarization. The optimal method is considered. Familiarization and study of these programming languages are conducted within the walls of one of the leading engineering universities of the Russian Federation, the Bauman Moscow State Technical University.